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Duan H, Shi R, Kang J, Banaschewski T, Bokde ALW, Büchel C, Desrivières S, Flor H, Grigis A, Garavan H, Gowland PA, Heinz A, Brühl R, Martinot JL, Martinot MLP, Artiges E, Nees F, Papadopoulos Orfanos D, Poustka L, Hohmann S, Holz N, Fröhner JH, Smolka MN, Vaidya N, Walter H, Whelan R, Schumann G, Lin X, Feng J. Population clustering of structural brain aging and its association with brain development. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.01.09.24301030. [PMID: 38260410 PMCID: PMC10802651 DOI: 10.1101/2024.01.09.24301030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Structural brain aging has demonstrated strong inter-individual heterogeneity and mirroring patterns with brain development. However, due to the lack of large-scale longitudinal neuroimaging studies, most of the existing research focused on the cross-sectional changes of brain aging. In this investigation, we present a data-driven approach that incorporate both cross-sectional changes and longitudinal trajectories of structural brain aging and identified two brain aging patterns among 37,013 healthy participants from UK Biobank. Participants with accelerated brain aging also demonstrated accelerated biological aging, cognitive decline and increased genetic susceptibilities to major neuropsychiatric disorders. Further, by integrating longitudinal neuroimaging studies from a multi-center adolescent cohort, we validated the "last in, first out" mirroring hypothesis and identified brain regions with manifested mirroring patterns between brain aging and brain development. Genomic analyses revealed risk loci and genes contributing to accelerated brain aging and delayed brain development, providing molecular basis for elucidating the biological mechanisms underlying brain aging and related disorders.
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Affiliation(s)
- Haojing Duan
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China
| | - Runye Shi
- School of Data Science, Fudan University, Shanghai, China
| | - Jujiao Kang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
| | - Arun L W Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | | | - Sylvane Desrivières
- Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Herta Flor
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
- Department of Psychology, School of Social Sciences, University of Mannheim, 68131 Mannheim, Germany
| | - Antoine Grigis
- NeuroSpin, CEA, Université Paris-Saclay, F-91191 Gif-sur-Yvette, France
| | - Hugh Garavan
- Departments of Psychiatry and Psychology, University of Vermont, 05405 Burlington, Vermont, USA
| | - Penny A Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, United Kingdom
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Rüdiger Brühl
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Jean-Luc Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U1299 "Developmental Trajectories and Psychiatry", Université Paris-Saclay, Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli, Gif-sur-Yvette, France
- Psychiatry Department, EPS Barthélémy Durand, Etampes; France
| | - Marie-Laure Paillère Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U1299 "Developmental Trajectories and Psychiatry", Université Paris-Saclay, Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli, Gif-sur-Yvette, France
- AP-HP. Sorbonne Université, Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, Paris, France
| | - Eric Artiges
- Institut National de la Santé et de la Recherche Médicale, INSERM U1299 "Developmental Trajectories and Psychiatry", Université Paris-Saclay, Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli, Gif-sur-Yvette, France
- Psychiatry Department, EPS Barthélémy Durand, Etampes; France
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
- Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig-Holstein Kiel University, Kiel, Germany
| | | | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, von-Siebold-Str. 5, 37075, Göttingen, Germany
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
| | - Nathalie Holz
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
| | - Juliane H Fröhner
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Michael N Smolka
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Nilakshi Vaidya
- Department of Psychiatry and Neurosciences, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität BerlinHumboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Ireland
| | - Gunter Schumann
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Department of Psychiatry and Neurosciences, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität BerlinHumboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
- Centre for Population Neuroscience and Stratified Medicine (PONS Centre), ISTBI, Fudan University, Shanghai, China
- Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin Berlin, Germany
| | - Xiaolei Lin
- School of Data Science, Fudan University, Shanghai, China
- Huashan Institute of Medicine, Huashan Hospital affiliated to Fudan University, Shanghai, China
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China
- School of Data Science, Fudan University, Shanghai, China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
- Zhangjiang Fudan International Innovation Center, Shanghai, China
- Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK
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2
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Chen J, Ngo A, Rodríguez-Cruces R, Royer J, Caligiuri ME, Gambardella A, Concha L, Keller SS, Cendes F, Yasuda CL, Alvim MKM, Bonilha L, Gleichgerrcht E, Focke NK, Kreilkamp B, Domin M, von Podewils F, Langner S, Rummel C, Wiest R, Martin P, Kotikalapudi R, Bender B, O’Brien TJ, Sinclair B, Vivash L, Kwan P, Desmond PM, Lui E, Duma GM, Bonanni P, Ballerini A, Vaudano AE, Meletti S, Tondelli M, Alhusaini S, Doherty CP, Cavalleri GL, Delanty N, Kälviäinen R, Jackson GD, Kowalczyk M, Mascalchi M, Semmelroch M, Thomas RH, Soltanian-Zadeh H, Davoodi-Bojd E, Zhang J, Lenge M, Guerrini R, Bartolini E, Hamandi K, Foley S, Rüber T, Bauer T, Weber B, Caldairou B, Depondt C, Absil J, Carr SJA, Abela E, Richardson MP, Devinsky O, Pardoe H, Severino M, Striano P, Tortora D, Kaestner E, Hatton SN, Arienzo D, Vos SB, Ryten M, Taylor PN, Duncan JS, Whelan CD, Galovic M, Winston GP, Thomopoulos SI, Thompson PM, Sisodiya SM, Labate A, McDonald CR, Caciagli L, Bernasconi N, Bernasconi A, Larivière S, Schrader D, Bernhardt BC. A WORLDWIDE ENIGMA STUDY ON EPILEPSY-RELATED GRAY AND WHITE MATTER COMPROMISE ACROSS THE ADULT LIFESPAN. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.02.583073. [PMID: 38496668 PMCID: PMC10942350 DOI: 10.1101/2024.03.02.583073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Objectives Temporal lobe epilepsy (TLE) is commonly associated with mesiotemporal pathology and widespread alterations of grey and white matter structures. Evidence supports a progressive condition although the temporal evolution of TLE is poorly defined. This ENIGMA-Epilepsy study utilized multimodal magnetic resonance imaging (MRI) data to investigate structural alterations in TLE patients across the adult lifespan. We charted both grey and white matter changes and explored the covariance of age-related alterations in both compartments. Methods We studied 769 TLE patients and 885 healthy controls across an age range of 17-73 years, from multiple international sites. To assess potentially non-linear lifespan changes in TLE, we harmonized data and combined median split assessments with cross-sectional sliding window analyses of grey and white matter age-related changes. Covariance analyses examined the coupling of grey and white matter lifespan curves. Results In TLE, age was associated with a robust grey matter thickness/volume decline across a broad cortico-subcortical territory, extending beyond the mesiotemporal disease epicentre. White matter changes were also widespread across multiple tracts with peak effects in temporo-limbic fibers. While changes spanned the adult time window, changes accelerated in cortical thickness, subcortical volume, and fractional anisotropy (all decreased), and mean diffusivity (increased) after age 55 years. Covariance analyses revealed strong limbic associations between white matter tracts and subcortical structures with cortical regions. Conclusions This study highlights the profound impact of TLE on lifespan changes in grey and white matter structures, with an acceleration of aging-related processes in later decades of life. Our findings motivate future longitudinal studies across the lifespan and emphasize the importance of prompt diagnosis as well as intervention in patients.
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Affiliation(s)
- Judy Chen
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Alexander Ngo
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Raúl Rodríguez-Cruces
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Jessica Royer
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | | | - Antonio Gambardella
- Neuroscience Research Center, University Magna Græcia, Catanzaro, CZ, Italy
- Institute of Neurology, University Magna Græcia, Catanzaro, CZ, Italy
| | - Luis Concha
- Institute of Neurobiology, Universidad Nacional Autónoma de México, Querétaro, México
| | - Simon S. Keller
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, United Kingdom
- Walton Centre NHS Foundation Trust, Liverpool, United Kingdom
| | - Fernando Cendes
- Department of Neurology, University of Campinas-–UNICAMP, Campinas, São Paulo, Brazil
| | - Clarissa L. Yasuda
- Department of Neurology, University of Campinas-–UNICAMP, Campinas, São Paulo, Brazil
| | - Marina K. M. Alvim
- Department of Neurology, University of Campinas-–UNICAMP, Campinas, São Paulo, Brazil
| | | | | | - Niels K. Focke
- Department of Neurology, University of Medicine Göttingen, Göttingen, Germany
| | - Barbara Kreilkamp
- Department of Neurology, University of Medicine Göttingen, Göttingen, Germany
| | - Martin Domin
- Institute of Diagnostic Radiology and Neuroradiology, Functional Imaging Unit, University Medicine Greifswald, Greifswald, Germany
| | - Felix von Podewils
- Department of Neurology, University Medicine Greifswald, Epilepsy Center, Greifswald, Germany
| | - Soenke Langner
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Christian Rummel
- Support Center for Advanced Neuroimaging (SCAN), University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Bern, Switzerland
| | - Roland Wiest
- Support Center for Advanced Neuroimaging (SCAN), University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Bern, Switzerland
| | - Pascal Martin
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Raviteja Kotikalapudi
- Department of Neurology, University of Medicine Göttingen, Göttingen, Germany
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Benjamin Bender
- Diagnostic and Interventional Neuroradiology, University Hospital Tübingen, Germany
| | - Terence J. O’Brien
- Department of Neuroscience, Central Clinical School, Alfred Hospital, Monash University, Melbourne, Victoria, Australia
- Departments of Medicine and Radiology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Benjamin Sinclair
- Department of Neuroscience, Central Clinical School, Alfred Hospital, Monash University, Melbourne, Victoria, Australia
- Departments of Medicine and Radiology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Lucy Vivash
- Department of Neuroscience, Central Clinical School, Alfred Hospital, Monash University, Melbourne, Victoria, Australia
- Departments of Medicine and Radiology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Patrick Kwan
- Departments of Medicine and Radiology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Patricia M. Desmond
- Departments of Medicine and Radiology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Elaine Lui
- Departments of Medicine and Radiology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Gian Marco Duma
- Scientific Institute IRCCS E.Medea, Epilepsy Unit, Conegliano (TV), Italy
| | - Paolo Bonanni
- Scientific Institute IRCCS E.Medea, Epilepsy Unit, Conegliano (TV), Italy
| | - Alice Ballerini
- Department of Biomedical, Metabolic and Neural Science, University of Modena and Reggio Emilia, Modena, Italy
| | - Anna Elisabetta Vaudano
- Neurology Unit, OCB Hospital, Azienda Ospedaliera-Universitaria, Modena, Italy
- Department of Biomedical, Metabolic and Neural Science, University of Modena and Reggio Emilia, Modena, Italy
| | - Stefano Meletti
- Neurology Unit, OCB Hospital, Azienda Ospedaliera-Universitaria, Modena, Italy
- Department of Biomedical, Metabolic and Neural Science, University of Modena and Reggio Emilia, Modena, Italy
| | - Manuela Tondelli
- Department of Biomedical, Metabolic and Neural Science, University of Modena and Reggio Emilia, Modena, Italy
- Primary Care Department, Azienda Sanitaria Locale di Modena, Modena, Italy
| | - Saud Alhusaini
- Department of Molecular and Cellular Therapeutics, The Royal College of Surgeons in Ireland, Dublin, Ireland
- Department of Neurology, Alpert Medical School of Brown University, Providence, RI, USA
| | - Colin P. Doherty
- Department of Neurology, St James’ Hospital, Dublin, Ireland
- FutureNeuro SFI Research Centre, Dublin, Ireland
| | - Gianpiero L. Cavalleri
- Department of Molecular and Cellular Therapeutics, The Royal College of Surgeons in Ireland, Dublin, Ireland
- FutureNeuro SFI Research Centre, Dublin, Ireland
| | - Norman Delanty
- Department of Molecular and Cellular Therapeutics, The Royal College of Surgeons in Ireland, Dublin, Ireland
- FutureNeuro SFI Research Centre, Dublin, Ireland
| | - Reetta Kälviäinen
- Epilepsy Center, Neuro Center, Kuopio University Hospital, Member of the European Reference Network for Rare and Complex Epilepsies EpiCARE, Kuopio, Finland
- Faculty of Health Sciences, School of Medicine, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Graeme D. Jackson
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne VIC 3010, Australia
| | - Magdalena Kowalczyk
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne VIC 3010, Australia
| | - Mario Mascalchi
- Neuroradiology Research Program, Meyer Children Hospital of Florence, University of Florence, Florence, Italy
| | - Mira Semmelroch
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne VIC 3010, Australia
| | - Rhys H. Thomas
- Transitional and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Hamid Soltanian-Zadeh
- Contol and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran
- Departments of Research Administration and Radiology, Henry Ford Health System, Detroit, MI, USA
| | | | - Junsong Zhang
- Cognitive Science Department, Xiamen University, Xiamen, China
| | - Matteo Lenge
- Child Neurology Unit and Laboratories, Neuroscience Department, Meyer Children’s Hospital IRCCS, Florence, Italy
| | - Renzo Guerrini
- Child Neurology Unit and Laboratories, Neuroscience Department, Meyer Children’s Hospital IRCCS, Florence, Italy
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Italy
| | | | - Khalid Hamandi
- Cardiff University Brain Research Imaging Centre (CUBRIC), College of Biomedical and Life Sciences, Cardiff University, Cardiff, UK
- The Welsh Epilepsy Unit, Department of Neurology, University Hospital of Wales, Cardiff, UK
| | - Sonya Foley
- Cardiff University Brain Research Imaging Centre (CUBRIC), College of Biomedical and Life Sciences, Cardiff University, Cardiff, UK
| | - Theodor Rüber
- Department of Neuroradiology, University Hospital Bonn, Bonn, Germany
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
| | - Tobias Bauer
- Department of Neuroradiology, University Hospital Bonn, Bonn, Germany
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
| | - Bernd Weber
- Institute of Experimental Epileptology and Cognition Research, University Hospital Bonn, Bonn, Germany
| | - Benoit Caldairou
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Chantal Depondt
- Department of Neurology, Hôpital Erasme, Hôpital Universitaire de Bruxelles (HUB), Université Libre de Bruxelles, Brussels, Belgium
| | - Julie Absil
- Department of Radiology, Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium
| | - Sarah J. A. Carr
- School of Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, UK
| | - Eugenio Abela
- School of Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, UK
| | - Mark P. Richardson
- School of Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, UK
| | - Orrin Devinsky
- Department of Neurology, NYU Grossman School of Medicine, New York, NY, United States
| | - Heath Pardoe
- Department of Neurology, NYU Grossman School of Medicine, New York, NY, United States
| | | | - Pasquale Striano
- IRCCS Istituto Giannina Gaslini, Genova, Italy
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genova, Genova, Italy
| | - Domenico Tortora
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genova, Genova, Italy
| | - Erik Kaestner
- Department of Radiation Medicine and Applied Sciences; Department of Psychiatry, Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, United States
| | - Sean N. Hatton
- Department of Neurosciences, Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, United States
| | - Donatello Arienzo
- Department of Radiation Medicine and Applied Sciences; Department of Psychiatry, Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, United States
| | - Sjoerd B. Vos
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- Chalfont Centre for Epilepsy, Bucks, UK
- Centre for Medical Image Computing, University College London, London, UK
| | - Mina Ryten
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Epilepsy Society, Chalfont St Peter, Bucks, UK
| | - Peter N. Taylor
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- CNNP Lab, ICOS group, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - John S. Duncan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- Chalfont Centre for Epilepsy, Bucks, UK
| | - Christopher D. Whelan
- Department of Molecular and Cellular Therapeutics, The Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Marian Galovic
- Department of Neurology, Clinical Neuroscience Center, University Hospital and University of Zürich, Zürich, Switzerland
| | - Gavin P. Winston
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- Chalfont Centre for Epilepsy, Bucks, UK
- Department of Medicine, Division of Neurology, Queen’s University, Kingston, ON, Canada
| | - Sophia I. Thomopoulos
- Imaging Genetics Center, Mark & Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Paul M. Thompson
- Imaging Genetics Center, Mark & Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Sanjay M. Sisodiya
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- Chalfont Centre for Epilepsy, Bucks, UK
| | - Angelo Labate
- Neurophysiopathology and Movement Disorders Clinic, Regional Epilepsy Center, University of Messina, Italy
| | - Carrie R. McDonald
- Department of Radiation Medicine and Applied Sciences; Department of Psychiatry, Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, United States
| | - Lorenzo Caciagli
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Epilepsy Society, Chalfont St Peter, Bucks, UK
| | - Neda Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Andrea Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Sara Larivière
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
- Center for Brain Circuit Therapeutics, Brigham and Women’s Hospital, Harvard University, Boston, MA, USA
| | - Dewi Schrader
- BC Children’s Hospital, University of British Columbia, Vancouver, BC, Canada
| | - Boris C. Bernhardt
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
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3
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Peraza JA, Salo T, Riedel MC, Bottenhorn KL, Poline JB, Dockès J, Kent JD, Bartley JE, Flannery JS, Hill-Bowen LD, Lobo RP, Poudel R, Ray KL, Robinson JL, Laird RW, Sutherland MT, de la Vega A, Laird AR. Methods for decoding cortical gradients of functional connectivity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.01.551505. [PMID: 37577598 PMCID: PMC10418206 DOI: 10.1101/2023.08.01.551505] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
Macroscale gradients have emerged as a central principle for understanding functional brain organization. Previous studies have demonstrated that a principal gradient of connectivity in the human brain exists, with unimodal primary sensorimotor regions situated at one end and transmodal regions associated with the default mode network and representative of abstract functioning at the other. The functional significance and interpretation of macroscale gradients remains a central topic of discussion in the neuroimaging community, with some studies demonstrating that gradients may be described using meta-analytic functional decoding techniques. However, additional methodological development is necessary to fully leverage available meta-analytic methods and resources and quantitatively evaluate their relative performance. Here, we conducted a comprehensive series of analyses to investigate and improve the framework of data-driven, meta-analytic methods, thereby establishing a principled approach for gradient segmentation and functional decoding. We found that a two-segment solution determined by a k-means segmentation approach and an LDA-based meta-analysis combined with the NeuroQuery database was the optimal combination of methods for decoding functional connectivity gradients. Finally, we proposed a method for decoding additional components of the gradient decomposition. The current work aims to provide recommendations on best practices and flexible methods for gradient-based functional decoding of fMRI data.
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Affiliation(s)
- Julio A. Peraza
- Department of Physics, Florida International University, Miami, FL, USA
| | - Taylor Salo
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Katherine L. Bottenhorn
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA
| | - Jean-Baptiste Poline
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Jérôme Dockès
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - James D. Kent
- Department of Psychology, University of Texas at Austin, Austin, TX, USA
| | | | - Jessica S. Flannery
- Department of Psychology and Neuroscience, University of North Carolina, Chapel Hill, NC, USA
| | | | | | - Ranjita Poudel
- Department of Health Outcomes and Behavior, Moffitt Cancer Center, Tampa, FL, USA
| | - Kimberly L. Ray
- Department of Psychology, University of Texas at Austin, Austin, TX, USA
| | | | - Robert W. Laird
- Department of Physics, Florida International University, Miami, FL, USA
| | | | | | - Angela R. Laird
- Department of Physics, Florida International University, Miami, FL, USA
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4
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Ricard JA, Labache L, Segal A, Dhamala E, Cocuzza CV, Jones G, Yip S, Chopra S, Holmes AJ. A shared spatial topography links the functional connectome correlates of cocaine use disorder and dopamine D 2/3 receptor densities. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.17.567591. [PMID: 38045392 PMCID: PMC10690146 DOI: 10.1101/2023.11.17.567591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
Background The biological mechanisms that contribute to cocaine and other substance use disorders involve an array of cortical and subcortical systems. Prior work on the development and maintenance of substance use has largely focused on cortico-striatal circuits, with relatively less attention on alterations within and across large-scale functional brain networks, and associated aspects of the dopamine system. The brain-wide pattern of temporal co-activation between distinct brain regions, referred to as the functional connectome, underpins individual differences in behavior. Critically, the functional connectome correlates of substance use and their specificity to dopamine receptor densities relative to other metabotropic receptors classes remains to be established. Methods We comprehensively characterized brain-wide differences in functional connectivity across multiple scales, including individual connections, regions, and networks in participants with cocaine use disorder (CUD; n=69) and healthy matched controls (n=62), Further, we studied the relationship between the observed functional connectivity signatures of CUD and the spatial distribution of a broad range of normative neurotransmitter receptor and transporter bindings as assessed through 18 different normative positron emission tomography (PET) maps. Results Our analyses identified a widespread profile of functional connectivity differences between individuals with CUD and matched healthy comparison participants (8.8% of total edges; 8,185 edges; p FWE =0.025). We largely find lower connectivity preferentially linking default network and subcortical regions, and higher within-network connectivity in the default network in participants with CUD. Furthermore, we find consistent and replicable associations between signatures of CUD and normative spatial density of dopamine D 2/3 receptors. Conclusions Our analyses revealed a widespread profile of altered connectivity in individuals with CUD that extends across the functional connectome and implicates multiple circuits. This profile is robustly coupled with normative dopamine D 2/3 receptors densities. Underscoring the translational potential of connectomic approaches for the study of in vivo brain functions, CUD- linked aspects of brain function were spatially coupled to disorder relevant neurotransmitter systems. Key Points Question: Are there group differences in whole brain functional connectivity between individuals with and without cocaine use disorder, and to what extent do these connectivity patterns relate to the spatial distribution of dopamine (D 2/3 ) receptor densities? Findings: The presence of cocaine use disorder is associated with brain-wide functional connectivity alterations that are spatially coupled to the density of dopamine (D 2/3 ) receptors. Meaning: A preferential and replicable link exists between the functional connectome correlates of cocaine use disorder and dopamine receptor densities across the brain.
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Sha Z, Warrier V, Bethlehem RA, Schultz LM, Merikangas A, Sun KY, Gur RC, Gur RE, Shinohara RT, Seidlitz J, Almasy L, Andreassen OA, Alexander-Bloch AF. The overlapping genetic architecture of psychiatric disorders and cortical brain structure. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.05.561040. [PMID: 37873315 PMCID: PMC10592957 DOI: 10.1101/2023.10.05.561040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Both psychiatric vulnerability and cortical structure are shaped by the cumulative effect of common genetic variants across the genome. However, the shared genetic underpinnings between psychiatric disorders and brain structural phenotypes, such as thickness and surface area of the cerebral cortex, remains elusive. In this study, we employed pleiotropy-informed conjunctional false discovery rate analysis to investigate shared loci across genome-wide association scans of regional cortical thickness, surface area, and seven psychiatric disorders in approximately 700,000 individuals of European ancestry. Aggregating regional measures, we identified 50 genetic loci shared between psychiatric disorders and surface area, as well as 26 genetic loci shared with cortical thickness. Risk alleles exhibited bidirectional effects on both cortical thickness and surface area, such that some risk alleles for each disorder increased regional brain size while other risk alleles decreased regional brain size. Due to bidirectional effects, in many cases we observed extensive pleiotropy between an imaging phenotype and a psychiatric disorder even in the absence of a significant genetic correlation between them. The impact of genetic risk for psychiatric disorders on regional brain structure did exhibit a consistent pattern across highly comorbid psychiatric disorders, with 80% of the genetic loci shared across multiple disorders displaying consistent directions of effect. Cortical patterning of genetic overlap revealed a hierarchical genetic architecture, with the association cortex and sensorimotor cortex representing two extremes of shared genetic influence on psychiatric disorders and brain structural variation. Integrating multi-scale functional annotations and transcriptomic profiles, we observed that shared genetic loci were enriched in active genomic regions, converged on neurobiological and metabolic pathways, and showed differential expression in postmortem brain tissue from individuals with psychiatric disorders. Cumulatively, these findings provide a significant advance in our understanding of the overlapping polygenic architecture between psychopathology and cortical brain structure.
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Affiliation(s)
- Zhiqiang Sha
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Varun Warrier
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Department of Psychology, University of Cambridge, Cambridge, UK
| | | | - Laura M. Schultz
- Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Lifespan Brain Institute, The Children’s Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
| | - Alison Merikangas
- Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Lifespan Brain Institute, The Children’s Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Kevin Y. Sun
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Lifespan Brain Institute, The Children’s Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
| | - Ruben C. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Pennsylvania, PA, 19104, USA
| | - Raquel E. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Pennsylvania, PA, 19104, USA
| | - Russell T. Shinohara
- Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, 423 Guardian Dr, Philadelphia, PA 19104, United States
- Center for Biomedical Image Computing and Analytics (CBICA), Department of Radiology, Perelman School of Medicine, United States
| | - Jakob Seidlitz
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Lifespan Brain Institute, The Children’s Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
| | - Laura Almasy
- Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Lifespan Brain Institute, The Children’s Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ole A. Andreassen
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Aaron F. Alexander-Bloch
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Lifespan Brain Institute, The Children’s Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
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Yu M, Risacher SL, Nho KT, Wen Q, Oblak AL, Unverzagt FW, Apostolova LG, Farlow MR, Brosch JR, Clark DG, Wang S, Deardorff R, Wu YC, Gao S, Sporns O, Saykin AJ. Spatial transcriptomic patterns underlying regional vulnerability to amyloid-β and tau pathologies and their relationships to cognitive dysfunction in Alzheimer's disease. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.08.12.23294017. [PMID: 37645867 PMCID: PMC10462206 DOI: 10.1101/2023.08.12.23294017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
Amyloid-β (Aβ) and tau proteins accumulate within distinct neuronal systems in Alzheimer's disease (AD). Although it is not clear why certain brain regions are more vulnerable to Aβ and tau pathologies than others, gene expression may play a role. We studied the association between brain-wide gene expression profiles and regional vulnerability to Aβ (gene-to-Aβ associations) and tau (gene-to-tau associations) pathologies leveraging two large independent cohorts (n = 715) of participants along the AD continuum. We identified several AD susceptibility genes and gene modules in a gene co-expression network with expression profiles related to regional vulnerability to Aβ and tau pathologies in AD. In particular, we found that the positive APOE -to-tau association was only seen in the AD cohort, whereas patients with AD and frontotemporal dementia shared similar positive MAPT -to-tau association. Some AD candidate genes showed sex-dependent negative gene-to-Aβ and gene-to-tau associations. In addition, we identified distinct biochemical pathways associated with the gene-to-Aβ and the gene-to-tau associations. Finally, we proposed a novel analytic framework, linking the identified gene-to-pathology associations to cognitive dysfunction in AD at the individual level, suggesting potential clinical implication of the gene-to-pathology associations. Taken together, our study identified distinct gene expression profiles and biochemical pathways that may explain the discordance between regional Aβ and tau pathologies, and filled the gap between gene-to-pathology associations and cognitive dysfunction in individual AD patients that may ultimately help identify novel personalized pathogenetic biomarkers and therapeutic targets. One Sentence Summary We identified replicable cognition-related associations between regional gene expression profiles and selectively regional vulnerability to amyloid-β and tau pathologies in AD.
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Issa LK, Sekaran NVC, Llano DA. Highly branched and complementary distributions of layer 5 and layer 6 auditory corticofugal axons in mouse. Cereb Cortex 2023; 33:9566-9582. [PMID: 37386697 PMCID: PMC10431747 DOI: 10.1093/cercor/bhad227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Revised: 06/05/2023] [Accepted: 06/06/2023] [Indexed: 07/01/2023] Open
Abstract
The auditory cortex exerts a powerful, yet heterogeneous, effect on subcortical targets. Auditory corticofugal projections emanate from layers 5 and 6 and have complementary physiological properties. While several studies suggested that layer 5 corticofugal projections branch widely, others suggested that multiple independent projections exist. Less is known about layer 6; no studies have examined whether the various layer 6 corticofugal projections are independent. Therefore, we examined branching patterns of layers 5 and 6 auditory corticofugal neurons, using the corticocollicular system as an index, using traditional and novel approaches. We confirmed that dual retrograde injections into the mouse inferior colliculus and auditory thalamus co-labeled subpopulations of layers 5 and 6 auditory cortex neurons. We then used an intersectional approach to relabel layer 5 or 6 corticocollicular somata and found that both layers sent extensive branches to multiple subcortical structures. Using a novel approach to separately label layers 5 and 6 axons in individual mice, we found that layers 5 and 6 terminal distributions partially spatially overlapped and that giant terminals were only found in layer 5-derived axons. Overall, the high degree of branching and complementarity in layers 5 and 6 axonal distributions suggest that corticofugal projections should be considered as 2 widespread systems, rather than collections of individual projections.
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Affiliation(s)
- Lina K Issa
- Department of Molecular and Integrative Physiology, University of Illinois at Urbana—Champaign, Champaign, IL, United States
- Beckman Institute for Advanced Science and Technology, Urbana, IL, United States
| | - Nathiya V C Sekaran
- Department of Molecular and Integrative Physiology, University of Illinois at Urbana—Champaign, Champaign, IL, United States
- Beckman Institute for Advanced Science and Technology, Urbana, IL, United States
| | - Daniel A Llano
- Department of Molecular and Integrative Physiology, University of Illinois at Urbana—Champaign, Champaign, IL, United States
- Beckman Institute for Advanced Science and Technology, Urbana, IL, United States
- Department of Biomedical and Translational Sciences, Carle Illinois College of Medicine, Urbana, IL, United States
- Department of Speech and Hearing Science, University of Illinois at Urbana-Champaign, Champaign, IL, United States
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Singleton SP, Timmermann C, Luppi AI, Eckernäs E, Roseman L, Carhart-Harris RL, Kuceyeski A. Time-resolved network control analysis links reduced control energy under DMT with the serotonin 2a receptor, signal diversity, and subjective experience. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.11.540409. [PMID: 37214949 PMCID: PMC10197635 DOI: 10.1101/2023.05.11.540409] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Psychedelics offer a profound window into the functioning of the human brain and mind through their robust acute effects on perception, subjective experience, and brain activity patterns. In recent work using a receptor-informed network control theory framework, we demonstrated that the serotonergic psychedelics lysergic acid diethylamide (LSD) and psilocybin flatten the brain's control energy landscape in a manner that covaries with more dynamic and entropic brain activity. Contrary to LSD and psilocybin, whose effects last for hours, the serotonergic psychedelic N,N-dimethyltryptamine (DMT) rapidly induces a profoundly immersive altered state of consciousness lasting less than 20 minutes, allowing for the entirety of the drug experience to be captured during a single resting-state fMRI scan. Using network control theory, which quantifies the amount of input necessary to drive transitions between functional brain states, we integrate brain structure and function to map the energy trajectories of 14 individuals undergoing fMRI during DMT and placebo. Consistent with previous work, we find that global control energy is reduced following injection with DMT compared to placebo. We additionally show longitudinal trajectories of global control energy correlate with longitudinal trajectories of EEG signal diversity (a measure of entropy) and subjective ratings of drug intensity. We interrogate these same relationships on a regional level and find that the spatial patterns of DMT's effects on these metrics are correlated with serotonin 2a receptor density (obtained from separately acquired PET data). Using receptor distribution and pharmacokinetic information, we were able to successfully recapitulate the effects of DMT on global control energy trajectories, demonstrating a proof-of-concept for the use of control models in predicting pharmacological intervention effects on brain dynamics.
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Affiliation(s)
| | - Christopher Timmermann
- Center for Psychedelic Research, Department of Brain Science, Imperial College London, London, United Kingdom
| | | | - Emma Eckernäs
- Unit for Pharmacokinetics and Drug Metabolism, Department of Pharmacology, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden
| | - Leor Roseman
- Center for Psychedelic Research, Department of Brain Science, Imperial College London, London, United Kingdom
| | - Robin L. Carhart-Harris
- Center for Psychedelic Research, Department of Brain Science, Imperial College London, London, United Kingdom
- Psychedelics Division, Neuroscape, University of California San Francisco, USA
| | - Amy Kuceyeski
- Department of Computational Biology, Cornell University, Ithaca, USA
- Department of Radiology, Weill Cornell Medicine, New York, USA
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Liu X, Huang H, Snutch TP, Cao P, Wang L, Wang F. The Superior Colliculus: Cell Types, Connectivity, and Behavior. Neurosci Bull 2022; 38:1519-1540. [PMID: 35484472 DOI: 10.1007/s12264-022-00858-1] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Accepted: 02/16/2022] [Indexed: 10/18/2022] Open
Abstract
The superior colliculus (SC), one of the most well-characterized midbrain sensorimotor structures where visual, auditory, and somatosensory information are integrated to initiate motor commands, is highly conserved across vertebrate evolution. Moreover, cell-type-specific SC neurons integrate afferent signals within local networks to generate defined output related to innate and cognitive behaviors. This review focuses on the recent progress in understanding of phenotypic diversity amongst SC neurons and their intrinsic circuits and long-projection targets. We further describe relevant neural circuits and specific cell types in relation to behavioral outputs and cognitive functions. The systematic delineation of SC organization, cell types, and neural connections is further put into context across species as these depend upon laminar architecture. Moreover, we focus on SC neural circuitry involving saccadic eye movement, and cognitive and innate behaviors. Overall, the review provides insight into SC functioning and represents a basis for further understanding of the pathology associated with SC dysfunction.
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Affiliation(s)
- Xue Liu
- Shenzhen Key Lab of Neuropsychiatric Modulation, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Key Laboratory of Brain Connectome and Manipulation, the Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, 518055, China.,University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Hongren Huang
- Shenzhen Key Lab of Neuropsychiatric Modulation, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Key Laboratory of Brain Connectome and Manipulation, the Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, 518055, China.,University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Terrance P Snutch
- Michael Smith Laboratories and Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, V6T 1Z4, Canada
| | - Peng Cao
- National Institute of Biological Sciences, Beijing, 100049, China
| | - Liping Wang
- Shenzhen Key Lab of Neuropsychiatric Modulation, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Key Laboratory of Brain Connectome and Manipulation, the Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, 518055, China.
| | - Feng Wang
- Shenzhen Key Lab of Neuropsychiatric Modulation, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Key Laboratory of Brain Connectome and Manipulation, the Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, 518055, China.
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10
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Cai X, Li L, Liu W, Du N, Zhao Y, Han Y, Liu C, Yin Y, Fu X, Sheng D, Yin L, Wang L, Wei P, Sheng X. A dual-channel optogenetic stimulator selectively modulates distinct defensive behaviors. iScience 2022; 25:103681. [PMID: 35036871 PMCID: PMC8749196 DOI: 10.1016/j.isci.2021.103681] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Revised: 11/14/2021] [Accepted: 12/21/2021] [Indexed: 01/22/2023] Open
Abstract
Implantable devices and systems have been emerging as powerful tools for neuroscience research and medical applications. Here we report a wireless, dual-channel optoelectronic system for functional optogenetic interrogation of superior colliculus (SC), a layered structure pertinent to defensive behaviors, in rodents. Specifically, a flexible and injectable probe comprises two thin-film microscale light-emitting diodes (micro-LEDs) at different depths, providing spatially resolved optical illuminations within the tissue. Under remote control, these micro-LEDs interrogate the intermediate layer and the deep layer of the SC (ILSC and DLSC) of the same mice, and deterministically evoke distinct freezing and flight behaviors, respectively. Furthermore, the system allows synchronized optical stimulations in both regions, and we discover that the flight response dominates animals' behaviors in our experiments. In addition, c-Fos immunostaining results further elucidate the functional hierarchy of the SC. These demonstrations provide a viable route to unraveling complex brain structures and functions. A wireless implant with two micro-LEDs enables dual-channel optogenetic stimulations Two micro-LEDs stimulate the intermediate and the deep layers of superior colliculus Dual-channel stimulations selectively evoke suppressed or promoted moving behaviors Synchronized stimulations in the intermediate and the deep layers are achieved
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Affiliation(s)
- Xue Cai
- Department of Electronic Engineering, Beijing National Research Center for Information Science and Technology, Center for Flexible Electronics Technology, and IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China
| | - Lizhu Li
- Department of Electronic Engineering, Beijing National Research Center for Information Science and Technology, Center for Flexible Electronics Technology, and IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China
| | - Wenhao Liu
- Shenzhen Key Lab of Neuropsychiatric Modulation and Collaborative Innovation Center for Brain Science, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Center for Excellence in Brain Science and Intelligence Technology, Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen-Hong Kong Institute of Brain Science, Shenzhen Fundamental Research Institutions, Shenzhen 518055, China.,Department of Biomedical Sciences, City University of Hong Kong, Kowloon Tong, Hong Kong 999077, China
| | - Nianzhen Du
- Department of Electronic Engineering, Beijing National Research Center for Information Science and Technology, Center for Flexible Electronics Technology, and IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China
| | - Yu Zhao
- Department of Electronic Engineering, Beijing National Research Center for Information Science and Technology, Center for Flexible Electronics Technology, and IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China
| | - Yaning Han
- Shenzhen Key Lab of Neuropsychiatric Modulation and Collaborative Innovation Center for Brain Science, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Center for Excellence in Brain Science and Intelligence Technology, Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen-Hong Kong Institute of Brain Science, Shenzhen Fundamental Research Institutions, Shenzhen 518055, China.,University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Changbo Liu
- School of Materials Science and Engineering, Hangzhou Innovation Institute, Beihang University, Beijing 100191, China
| | - Yan Yin
- Department of Electronic Engineering, Beijing National Research Center for Information Science and Technology, Center for Flexible Electronics Technology, and IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China
| | - Xin Fu
- School of Materials Science and Engineering, Tsinghua University, Beijing 100084, China
| | - Dawid Sheng
- Department of Electronic Engineering, Beijing National Research Center for Information Science and Technology, Center for Flexible Electronics Technology, and IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China
| | - Lan Yin
- School of Materials Science and Engineering, Tsinghua University, Beijing 100084, China
| | - Liping Wang
- Shenzhen Key Lab of Neuropsychiatric Modulation and Collaborative Innovation Center for Brain Science, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Center for Excellence in Brain Science and Intelligence Technology, Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen-Hong Kong Institute of Brain Science, Shenzhen Fundamental Research Institutions, Shenzhen 518055, China
| | - Pengfei Wei
- Shenzhen Key Lab of Neuropsychiatric Modulation and Collaborative Innovation Center for Brain Science, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Center for Excellence in Brain Science and Intelligence Technology, Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen-Hong Kong Institute of Brain Science, Shenzhen Fundamental Research Institutions, Shenzhen 518055, China
| | - Xing Sheng
- Department of Electronic Engineering, Beijing National Research Center for Information Science and Technology, Center for Flexible Electronics Technology, and IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China
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Yudintsev G, Asilador AR, Sons S, Vaithiyalingam Chandra Sekaran N, Coppinger M, Nair K, Prasad M, Xiao G, Ibrahim BA, Shinagawa Y, Llano DA. Evidence for Layer-Specific Connectional Heterogeneity in the Mouse Auditory Corticocollicular System. J Neurosci 2021; 41:9906-9918. [PMID: 34670851 PMCID: PMC8638684 DOI: 10.1523/jneurosci.2624-20.2021] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Revised: 10/07/2021] [Accepted: 10/07/2021] [Indexed: 11/21/2022] Open
Abstract
The auditory cortex (AC) sends long-range projections to virtually all subcortical auditory structures. One of the largest and most complex of these-the projection between AC and inferior colliculus (IC; the corticocollicular pathway)-originates from layer 5 and deep layer 6. Though previous work has shown that these two corticocollicular projection systems have different physiological properties and network connectivities, their functional organization is poorly understood. Here, using a combination of traditional and viral tracers combined with in vivo imaging in both sexes of the mouse, we observed that layer 5 and layer 6 corticocollicular neurons differ in their areas of origin and termination patterns. Layer 5 corticocollicular neurons are concentrated in primary AC, while layer 6 corticocollicular neurons emanate from broad auditory and limbic areas in the temporal cortex. In addition, layer 5 sends dense projections of both small and large (>1 µm2 area) terminals to all regions of nonlemniscal IC, while layer 6 sends small terminals to the most superficial 50-100 µm of the IC. These findings suggest that layer 5 and 6 corticocollicular projections are optimized to play distinct roles in corticofugal modulation. Layer 5 neurons provide strong, rapid, and unimodal feedback to the nonlemniscal IC, while layer 6 neurons provide heteromodal and limbic modulation diffusely to the nonlemniscal IC. Such organizational diversity in the corticocollicular pathway may help to explain the heterogeneous effects of corticocollicular manipulations and, given similar diversity in corticothalamic pathways, may be a general principle in top-down modulation.SIGNIFICANCE STATEMENT We demonstrate that a major descending system in the brain is actually two systems. That is, the auditory corticocollicular projection, which exerts considerable influence over the midbrain, comprises two projections: one from layer 5 and the other from layer 6. The layer 6 projection is diffusely organized, receives multisensory inputs, and ends in small terminals; while the layer 5 projection is derived from a circumscribed auditory cortical area and ends in large terminals. These data suggest that the varied effects of cortical manipulations on the midbrain may be related to effects on two disparate systems. These findings have broader implications because other descending systems derive from two layers. Therefore, a duplex organization may be a common motif in descending control.
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Affiliation(s)
- Georgiy Yudintsev
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
- Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Alexander R Asilador
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
- Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Stacy Sons
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
- Department of Molecular and Integrative Physiology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Nathiya Vaithiyalingam Chandra Sekaran
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
- Department of Molecular and Integrative Physiology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Macey Coppinger
- Department of Molecular and Integrative Physiology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Kavya Nair
- Department of Molecular and Integrative Physiology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Masumi Prasad
- Department of Molecular and Integrative Physiology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Gang Xiao
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
- Department of Molecular and Integrative Physiology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Baher A Ibrahim
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
- Department of Molecular and Integrative Physiology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Yoshitaka Shinagawa
- Department of Molecular and Integrative Physiology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Daniel A Llano
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
- Department of Molecular and Integrative Physiology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
- Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
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Bertero A, Garcia C, Apicella AJ. Corticofugal VIP Gabaergic Projection Neurons in the Mouse Auditory and Motor Cortex. Front Neural Circuits 2021; 15:714780. [PMID: 34366798 PMCID: PMC8343102 DOI: 10.3389/fncir.2021.714780] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Accepted: 07/05/2021] [Indexed: 11/21/2022] Open
Abstract
Anatomical and physiological studies have described the cortex as a six-layer structure that receives, elaborates, and sends out information exclusively as excitatory output to cortical and subcortical regions. This concept has increasingly been challenged by several anatomical and functional studies that showed that direct inhibitory cortical outputs are also a common feature of the sensory and motor cortices. Similar to their excitatory counterparts, subsets of Somatostatin- and Parvalbumin-expressing neurons have been shown to innervate distal targets like the sensory and motor striatum and the contralateral cortex. However, no evidence of long-range VIP-expressing neurons, the third major class of GABAergic cortical inhibitory neurons, has been shown in such cortical regions. Here, using anatomical anterograde and retrograde viral tracing, we tested the hypothesis that VIP-expressing neurons of the mouse auditory and motor cortices can also send long-range projections to cortical and subcortical areas. We were able to demonstrate, for the first time, that VIP-expressing neurons of the auditory cortex can reach not only the contralateral auditory cortex and the ipsilateral striatum and amygdala, as shown for Somatostatin- and Parvalbumin-expressing long-range neurons, but also the medial geniculate body and both superior and inferior colliculus. We also demonstrate that VIP-expressing neurons of the motor cortex send long-range GABAergic projections to the dorsal striatum and contralateral cortex. Because of its presence in two such disparate cortical areas, this would suggest that the long-range VIP projection is likely a general feature of the cortex’s network.
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Affiliation(s)
- Alice Bertero
- Department of Biology, Neurosciences Institute, University of Texas at San Antonio, San Antonio, TX, United States
| | - Charles Garcia
- Department of Biology, Neurosciences Institute, University of Texas at San Antonio, San Antonio, TX, United States
| | - Alfonso Junior Apicella
- Department of Biology, Neurosciences Institute, University of Texas at San Antonio, San Antonio, TX, United States
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Bertero A, Zurita H, Normandin M, Apicella AJ. Auditory Long-Range Parvalbumin Cortico-Striatal Neurons. Front Neural Circuits 2020; 14:45. [PMID: 32792912 PMCID: PMC7390902 DOI: 10.3389/fncir.2020.00045] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Accepted: 06/29/2020] [Indexed: 11/13/2022] Open
Abstract
Previous studies have shown that cortico-striatal pathways link auditory signals to action-selection and reward-learning behavior through excitatory projections. Only recently it has been demonstrated that long-range GABAergic cortico-striatal somatostatin-expressing neurons in the auditory cortex project to the dorsal striatum, and functionally inhibit the main projecting neuronal population, the spiny projecting neuron. Here we tested the hypothesis that parvalbumin-expressing neurons of the auditory cortex can also send long-range projections to the auditory striatum. To address this fundamental question, we took advantage of viral and non-viral anatomical tracing approaches to identify cortico-striatal parvalbumin neurons (CS-Parv inhibitory projections → auditory striatum). Here, we describe their anatomical distribution in the auditory cortex and determine the anatomical and electrophysiological properties of layer 5 CS-Parv neurons. We also analyzed their characteristic voltage-dependent membrane potential gamma oscillation, showing that intrinsic membrane mechanisms generate them. The inherent membrane mechanisms can also trigger intermittent and irregular bursts (stuttering) of the action potential in response to steps of depolarizing current pulses.
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Affiliation(s)
- Alice Bertero
- Department of Biology, Neurosciences Institute, The University of Texas at San Antonio, San Antonio, TX, United States
| | - Hector Zurita
- Department of Biology, Neurosciences Institute, The University of Texas at San Antonio, San Antonio, TX, United States
| | - Marc Normandin
- Department of Biology, Neurosciences Institute, The University of Texas at San Antonio, San Antonio, TX, United States
| | - Alfonso Junior Apicella
- Department of Biology, Neurosciences Institute, The University of Texas at San Antonio, San Antonio, TX, United States
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Slater BJ, Sons SK, Yudintsev G, Lee CM, Llano DA. Thalamocortical and Intracortical Inputs Differentiate Layer-Specific Mouse Auditory Corticocollicular Neurons. J Neurosci 2019; 39:256-270. [PMID: 30361396 PMCID: PMC6325253 DOI: 10.1523/jneurosci.3352-17.2018] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2017] [Revised: 10/10/2018] [Accepted: 10/12/2018] [Indexed: 11/21/2022] Open
Abstract
Long-range descending projections from the auditory cortex play key roles in shaping response properties in the inferior colliculus. The auditory corticocollicular projection is massive and heterogeneous, with axons emanating from cortical layers 5 and 6, and plays a key role in directing plastic changes in the inferior colliculus. However, little is known about the cortical and thalamic networks within which corticocollicular neurons are embedded. Here, laser scanning photostimulation glutamate uncaging and photoactivation of channelrhodopsin-2 were used to probe the local and long-range network differences between preidentified layer 5 and layer 6 auditory corticocollicular neurons from male and female mice in vitro Layer 5 corticocollicular neurons were found to vertically integrate supragranular excitatory and inhibitory input to a substantially greater degree than their layer 6 counterparts. In addition, all layer 5 corticocollicular neurons received direct and large thalamic inputs from channelrhodopsin-2-labeled thalamocortical fibers, whereas such inputs were less common in layer 6 corticocollicular neurons. Finally, a new low-calcium/synaptic blockade approach to separate direct from indirect inputs using laser photostimulation was validated. These data demonstrate that layer 5 and 6 corticocollicular neurons receive distinct sets of cortical and thalamic inputs, supporting the hypothesis that they have divergent roles in modulating the inferior colliculus. Furthermore, the direct connection between the auditory thalamus and layer 5 corticocollicular neurons reveals a novel and rapid link connecting ascending and descending pathways.SIGNIFICANCE STATEMENT Descending projections from the cortex play a critical role in shaping the response properties of sensory neurons. The projection from the auditory cortex to the inferior colliculus is a massive, yet poorly understood, pathway emanating from two distinct cortical layers. Here we show, using a range of optical techniques, that mouse auditory corticocollicular neurons from different layers are embedded into different cortical and thalamic networks. Specifically, we observed that layer 5 corticocollicular neurons integrate information across cortical lamina and receive direct thalamic input. The latter connection provides a hyperdirect link between acoustic sensation and descending control, thus demonstrating a novel mechanism for rapid "online" modulation of sensory perception.
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Affiliation(s)
- Bernard J Slater
- Neuroscience Program and
- Beckman Institute for Advanced Science and Technology, Urbana, Illinois 61801
| | - Stacy K Sons
- Department of Molecular and Integrative Physiology, University of Illinois Urbana-Champaign, Urbana, Illinois 61801, and
- Beckman Institute for Advanced Science and Technology, Urbana, Illinois 61801
| | - Georgiy Yudintsev
- Neuroscience Program and
- Beckman Institute for Advanced Science and Technology, Urbana, Illinois 61801
| | - Christopher M Lee
- Department of Molecular and Integrative Physiology, University of Illinois Urbana-Champaign, Urbana, Illinois 61801, and
- Beckman Institute for Advanced Science and Technology, Urbana, Illinois 61801
| | - Daniel A Llano
- Neuroscience Program and
- Department of Molecular and Integrative Physiology, University of Illinois Urbana-Champaign, Urbana, Illinois 61801, and
- Beckman Institute for Advanced Science and Technology, Urbana, Illinois 61801
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15
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Moore B, Li K, Kaas JH, Liao CC, Boal AM, Mavity-Hudson J, Casagrande V. Cortical projections to the two retinotopic maps of primate pulvinar are distinct. J Comp Neurol 2018; 527:577-588. [PMID: 30078198 DOI: 10.1002/cne.24515] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2018] [Revised: 07/20/2018] [Accepted: 07/23/2018] [Indexed: 01/07/2023]
Abstract
Comprised of at least five distinct nuclei, the pulvinar complex of primates includes two large visually driven nuclei; one in the dorsal (lateral) pulvinar and one in the ventral (inferior) pulvinar, that contain similar retinotopic representations of the contralateral visual hemifield. Both nuclei also appear to have similar connections with areas of visual cortex. Here we determined the cortical connections of these two nuclei in galagos, members of the stepsirrhine primate radiation, to see if the nuclei differed in ways that could support differences in function. Injections of different retrograde tracers in each nucleus produced similar patterns of labeled neurons, predominately in layer 6 of V1, V2, V3, MT, regions of temporal cortex, and other visual areas. More complete labeling of neurons with a modified rabies virus identified these neurons as pyramidal cells with apical dendrites extending into superficial cortical layers. Importantly, the distributions of cortical neurons projecting to each of the two nuclei were highly overlapping, but formed separate populations. Sparse populations of double-labeled neurons were found in both V1 and V2 but were very low in number (<0.1%). Finally, the labeled cortical neurons were predominately in layer 6, and layer 5 neurons were labeled only in extrastriate areas. Terminations of pulvinar projections to area 17 was largely in superficial cortical layers, especially layer 1.
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Affiliation(s)
- Brandon Moore
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, Tennessee
| | - Keji Li
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, Tennessee.,Department of Cellular and Developmental Biology, Vanderbilt University, Nashville, Tennessee
| | - Jon H Kaas
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, Tennessee.,Department of Psychology, Vanderbilt University, Nashville, Tennessee
| | - Chia-Chi Liao
- Department of Psychology, Vanderbilt University, Nashville, Tennessee
| | - Andrew M Boal
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, Tennessee
| | | | - Vivien Casagrande
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, Tennessee.,Department of Cellular and Developmental Biology, Vanderbilt University, Nashville, Tennessee.,Department of Psychology, Vanderbilt University, Nashville, Tennessee
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Specialized Subpopulations of Deep-Layer Pyramidal Neurons in the Neocortex: Bridging Cellular Properties to Functional Consequences. J Neurosci 2018; 38:5441-5455. [PMID: 29798890 DOI: 10.1523/jneurosci.0150-18.2018] [Citation(s) in RCA: 93] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2018] [Revised: 05/09/2018] [Accepted: 05/11/2018] [Indexed: 12/25/2022] Open
Abstract
Neocortical pyramidal neurons with somata in layers 5 and 6 are among the most visually striking and enigmatic neurons in the brain. These deep-layer pyramidal neurons (DLPNs) integrate a plethora of cortical and extracortical synaptic inputs along their impressive dendritic arbors. The pattern of cortical output to both local and long-distance targets is sculpted by the unique physiological properties of specific DLPN subpopulations. Here we revisit two broad DLPN subpopulations: those that send their axons within the telencephalon (intratelencephalic neurons) and those that project to additional target areas outside the telencephalon (extratelencephalic neurons). While neuroscientists across many subdisciplines have characterized the intrinsic and synaptic physiological properties of DLPN subpopulations, our increasing ability to selectively target and manipulate these output neuron subtypes advances our understanding of their distinct functional contributions. This Viewpoints article summarizes our current knowledge about DLPNs and highlights recent work elucidating the functional differences between DLPN subpopulations.
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